Results 51 to 60 of about 915,441 (269)
An empirical analysis of the shift and scale parameters in BatchNorm
Batch Normalization (BatchNorm) is a technique that improves the training of deep neural networks, especially Convolutional Neural Networks (CNN). It has been empirically demonstrated that BatchNorm increases performance, stability, and accuracy, although the reasons for such improvements are unclear.
Peerthum, Yashna, Stamp, Mark
openaire +4 more sources
Peripheral lysosomes recruit PLEKHG3 to focal adhesions and restrain protrusion dynamics
Proximity‐dependent labeling at the LAMTOR complex revealed the Rho GEF PLEKHG3 as a lysosome‐proximal protein directing the study toward the influence of lysosome positioning on actin dynamics and cell motility. We show that PLEKHG3 colocalizes with lysosomes at focal adhesion sites and observe that forced peripheral dispersion of lysosomes hinders ...
Rainer Ettelt +8 more
wiley +1 more source
Golgi enzymes are retrieved from the plasma membrane to the trans‐Golgi network
Golgi enzymes are traditionally considered resident proteins retained within the Golgi apparatus. Here, we demonstrate that a subset transiently reaches the cell surface and is subsequently retrieved to the trans‐Golgi network via retrograde transport. Using a nanobody‐based toolkit, we uncover a dynamic trafficking cycle of several Golgi enzymes.
Dominik P. Buser, Tina Junne
wiley +1 more source
Sequential Probabilistic Ratio Test for the Scale Parameter of the P-Norm Distribution
We consider a series of independent observations from a P-norm distribution with the position parameter μ and the scale parameter σ. We test the simple hypothesis H0:σ=σ1 versus H1: σ=σ2.
Huan Ren, Hongchang Hu, Zhen Zeng
doaj +1 more source
Obesity raises blood levels of PAI‐1, a protein linked to metabolic dysfunction‐associated steatotic liver disease in people with obesity. In female mice fed a high‐fat diet, partially lowering PAI‐1 led to smaller subcutaneous fat cells and lower liver cholesterol, without changing body weight or insulin sensitivity.
Claudia E. Ramirez Bustamante +10 more
wiley +1 more source
Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry
EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri +5 more
wiley +1 more source
Emerging experimental and computational methods for studying redox‐regulated structural transitions
Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
Investigation of scale parameter for the Weibull-Chen distribution
Within this article, we estimate the scale parameter for the Weibull-Chen distribution and calculate posterior distributions. This analysis involves the application of the Bayesian technique, which utilizes two non-informative priors along with three ...
Mohamed Mubarak, Fathy H. Riad
doaj +1 more source
Synergistic perspectives—How single‐molecule biophysics complement biochemical understanding
In this review, we discuss how ensemble biochemistry and single‐molecule approaches are complementary, outline commonly used single‐molecule techniques, and illustrate their relevance through two representative case studies: chromatin organization by SMC complexes and pathway choice during DNA double‐strand break repair.
Sara De Bragança +2 more
wiley +1 more source
Unbiased Estimation of Location and Scale Parameters
It is well-known that there is a close connection between linear functionals on an appropriate Banach space and unbiased estimators. In Section 2 we prove some results concerning unbiased estimation of location and scale parameters. As application of these results we consider the case of Cauchy density with unknown location [scale] but known scale ...
Ghosh, J. K., Singh, Rajinder
openaire +3 more sources

